Evidence map›Paper›PMID 35513921›Full record

ReviewJournal of the National Medical Association2022

Understanding the social determinants of health and genetic factors contributing to the differences observed in COVID-19 incidence and mortality between underrepresented and other communities.

Jeslyn Rodriguez, Yuri Quintana

Open access · greenAbstract readReview
In one paragraph

Review in Journal of the National Medical Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jeslyn RodriguezAlbany Medical College, Albany, NY 12208, USA; Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, USA. Electronic address: rodrigj21@amc.edu.
Yuri QuintanaDivision of Clinical Informatics, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA; Harvard Medical School, Harvard University, Boston, MA, 02115, USA.
Beth Israel Deaconess Medical Center · US

Funding

BIDIRECTIONAL TRAINING TO ENHANCE CANCER RESEARCH CAPACITY IN AFRICAD43CA260640 · NCI · DANA-FARBER CANCER INST · PI REBBECK, TIMOTHY RICHARD · 2021 to 2025
$1.4M
NCI NIH HHS D43 CA260640
6 · The paper itself

Abstract

COVID-19 has been a devastating disease, especially in underserved communities. Data has shown that Indigenous peoples, Latinx communities, and Black Americans have a 3.3, 2.4, and 2 times higher mortality rate than White communities, respectively, due to COVID-19. Therefore, in this paper, we sought to understand how Social Determinants of Health and genetic factors influence COVID-19 incidence, mortality rates, and complications by assessing existing literature. Studies showed that identifying with a racial/ethnic minority, being homeless, housing insecurity, lower household median income, and living in an area with decreased air quality were associated with higher incidence and mortality from COVID-19. Analyses of these studies also showed a lack of resources to collect patients' social determinants of health, revealing an urgent need to create databases with information on local support programs and operationalize the referral and tracking outcomes to address the health inequities for Black, Indigenous, and Latinx communities.

Indexed as

COVID-19EthnicityHumansIncidenceMinority GroupsSocial Determinants of HealthCoronavirusCOVID-19IncidenceInequalityMortalitySocial determinants of health

Identifiers

PMID35513921
PMCPMC9060259
OpenAlexW4225293154

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.